Unveiling the Power of Generative AI in Revolutionizing Customer Experience

The explosion of interest around ChatGPT has been exciting to watch. The initial buzz continues to accelerate as consumers — for the first time really — interact directly with AI in a conversational manner.

While AI is having a big impact on all industries, customer experience (CX) seems to be emerging as one of the first use cases for this technology at scale. Gartner predicts that customer service innovation, including the emergence of generative AI and conversational AI enhancements, will drive contact center investment—with global spending growing to $38.9 billion in 2027. 

To better understand what is coming next, I spoke to Chaitanya Chokkareddy, Chief Product Officer at Ozonetel, a leading omnichannel CX platform provider. As the architect of one of the few full-stack CX platforms with deep AI and omnichannel contact center capabilities, Chaitanya works with some of India’s largest enterprises and startups and has an insider view into the changing role of customer experience.  

Together, we investigate how generative AI and foundation models are transforming conversational AI capabilities. What does this mean for businesses? How can customer experience leaders successfully integrate and leverage these powerful capabilities? What are the limitations and risks? This editorial captures key insights from our conversation. It explores the current state of technology, fundamental gaps we need to address, and the path ahead. 

Generative AI: From Availability to Adoption 

For people in the know, neither ChatGPT nor large language models are something new. As Chaitanya reminds us, GPT was launched almost three years back as an API. But the moment OpenAI made it free and replaced the API with a chat interface, it became mainstream.  

Today, both the technology and the user base are ready, which means the conditions are ideal for a radical transformation. 

Chaitanya has witnessed this cycle of change before. Having pioneered India’s first cloud telephony platform (2009) and cloud contact center solution (2011), he was instrumental in helping the cloud disrupt the on-premise contact center models and transform CX. He has watched the focus shift from call centers to contact centers to a broader view of customer experience. What is important to remember is that, throughout these radical shifts, technology was only the enabler.  

At its core, excellent CX continues to be all about communication with customers. And even as the industry considers the capabilities of AI, this focus will remain constant, that is, communication. 

What will change, however, is the efficiency and scale at which you can deliver this customer experience. For example, many of the brands Ozonetel works with handle hundreds of thousands of calls daily. Yet, a surface analysis reveals that over 80% of these calls are regular, repetitive queries.  

The business logic would be to figure out how you can realize efficiencies. Would you rather put a human to do this same task repeatedly? A human might also get bored! In fact, this is a key reason why contact centers have the highest attrition rates of all industries. Generative AI, promises Chaitanya, will free up humans to do more interesting and important work.
AI in the Contact Center: Beyond Cost Cutting 

When it comes to discovering efficiencies, Chaitanya cautions against focusing on cost reduction alone. “Everyone talks about cost reduction, process reduction, laying off people, etc. But I want to drill down into the outcomes that AI can provide outside of cost.” 

This thinking, he finds, often stems from looking at the contact center as a cost center — a myopic, one-sided view that he knows isn't shared by all the stakeholders. For instance, sales and marketing heads know how they can leverage contact centers and communication technology to increase revenue. And these leaders will optimize AI to boost growth and revenue. 

Take the simple example of how generative AI can improve call pick-up rates. When customers call, they expect an instant response — something many companies are unable to offer even today. AI has the potential to solve this. It can automate calls and reduce call queues, all while retaining a unique CX touch. Generative AI, for instance, makes it possible to have a much-adored celebrity “answer” customer queries, play a customer’s favourite song while on hold, or enable conversations with agents or bots who exude the familiarity of a close friend.  

In other words, there is scope for both innovation and personalization.  

AI can help businesses analyze vast amounts of consumer data, proactively anticipate pain points and future complaints, offering hyper personalized experiences based on their behavior, preferences, and past interactions. In short, companies can leverage AI to build a predictive, analytical ecosystem around their customers.  

Risks, Precautions, and Current Solutions 

While generative AI is promising, leaders must tread with caution. There are valid data privacy concerns and risks, and the technology models need to improve. Today, for example, models still “hallucinate,” or give wrong answers. And companies cannot control or make them speak in a certain way. These are all unsolved problems.  

And then there is the big question of customer data. As a business, you are accountable for your customers’ data. There should be no way that a customer, speaking with your bot, should be able to access any other customers’ data, even by accident. 

With these considerations in mind, leaders must realize that, at this stage, humans are still required to monitor bots. In fact, a human-AI partnership is the best way forward.  
AI that is agent-facing rather than customer-facing can give a business all the benefits of speed, hyper personalization, superior knowledge management, and advanced analytics with lower risks and errors.

The Big Question of Data

In India, businesses face one additional challenge when it comes to adopting AI. As of today, all large foundation models are hosted in the U.S., which hinders regulation. With restrictions around sending data out of the country, how can you use these AI models if they are hosted outside the country? Even if they launch operations within India, how would you ensure that your data stays with you? For contact centers and other highly regulated industries, this is a big hurdle.  
These are the kind of challenges that Chaitanya is trying to solve within Ozonetel – building a foundational model for India, within India, so that enterprises can have more control over their data, enabling them to innovate freely while remaining compliant and secure.  

The Road Ahead is Hybrid 

Today, Ozonetel has integrated ChatGPT to transform AI orchestration in contact centers. Generative AI is powering their conversational intelligence, quality audits, voice and chatbots, and neural search knowledge base.

This is just the beginning, and there is a long road ahead. While business leaders cannot deny the benefits of AI, they need to understand the risks and challenges. The solution right now is to keep the human aspect intact in places where control is needed. Think of it as a hybrid model where you automate other tasks to enhance productivity but retain humans to bring in the perception and thinking elements. 

Bottomline: generative AI isn’t a fad anymore. It’s here to stay. But despite its impressive capabilities, the ultimate accountability must lie with humans. If businesses take the right approach – establishing guardrails and encouraging innovation – they can leverage AI to build exceptional customer experiences and drive significant growth.